Search Results (1,042)

Objective: This study aimed to investigate the prognostic value of the preoperative monocyte-to-high-density lipoprotein cholesterol ratio (MHR) and clinicopathological parameters for predicting survival outcomes in patients undergoing curative-intent gastrectomy for gastric adenocarcinoma. Methods: This retrospective cohort study analyzed data from 304 patients with histopathologically confirmed gastric adenocarcinoma who underwent curative-intent gastrectomy with standardized D1+ or D2 lymphadenectomy. The MHR was calculated using preoperative monocyte counts and HDL cholesterol levels. Patients were dichotomized based on the optimal MHR cutoff determined via receiver operating characteristic curve analysis with the Youden index. Survival outcomes, including overall survival (OS) and progression-free survival (PFS), were assessed using Kaplan–Meier analysis and compared with log-rank tests. Results: ROC analysis determined an optimal MHR cutoff of ≥11.02 (AUC: 0.654; 95% CI: 0.59–0.718), yielding sensitivities and specificities of 62.6% and 62.4%, respectively. Patients with an elevated MHR (≥11.02) had worse 5-year OS (51.4 vs. 72.2%; p < 0.001) and PFS (65.2 vs. 80.5%; p = 0.003). In the multivariate Cox regression model, elevated MHR emerged as an independent predictor of disease progression (HR: 1.93; 95% CI: 1.17–3.18; p = 0.010), while parameters such as signet ring cell histology, lymphovascular invasion, and perineural invasion were significant in univariate analyses but not in the adjusted multivariate model. Conclusions: MHR should not be regarded as a definitive predictor in isolation but rather as a cost-effective, readily obtainable adjunct within a broader preoperative risk assessment framework. Integration with other inflammation-based and clinicopathological factors may enhance predictive performance and clinical applicability. Full article

Background and Purpose: Spontaneous intracerebral hemorrhage (ICH) is associated with high rates of morbidity and mortality. Early hematoma expansion (HE) is a key driver of poor outcomes, yet readily available non-contrast CT (NCCT) markers remain underused. We assessed four predefined NCCT signs—Blend Sign (BS), Black Hole Sign (BHS), Irregular Shape (IRS), and Satellite Sign (SS)—and a simple composite score (SUM_BBIS, 0–4) for their association with HE and in-hospital mortality. Methods: We retrospectively analyzed 404 consecutive adults with primary spontaneous ICH admitted to a tertiary-care center between January 2017 and December 2023. Patients with secondary causes of hemorrhage or without follow-up NCCT were excluded. Each sign was scored dichotomously by blinded readers and summed to form the SUM_BBIS. HE was defined as a >6 mL or >33% volume increase on repeat NCCT within 24–48 h. Outcomes included HE and in-hospital mortality; secondary analyses explored relationships with baseline hematoma volume, location, intraventricular extension (IVH), and comorbidities. Results: Among 404 patients, Irregular Shape was most frequent (62.1%), followed by Satellite Sign (34.9%), Black Hole Sign (31.1%), and Blend Sign (15.3%). Hematoma expansion occurred in 22.0% (89/404). Expansion was more common when ≥1 sign was present, with the Black Hole Sign showing the strongest association (56.2% vs. 23.8%; p < 0.001). In-hospital mortality rose stepwise with higher SUM_BBIS (mean 1.95 in non-survivors vs. 0.93 in survivors; p < 0.001). Conclusions: The four predefined NCCT signs, particularly BHS, identify ICH patients at increased risk of HE and in-hospital death. A simple, purely imaging-based composite (SUM_BBIS) captures cumulative radiological complexity and stratifies risk in a stepwise manner. Systematic evaluation of these markers may enhance early triage and inform timely therapeutic decisions, especially in emergency and resource-limited settings. Full article

Among the leading causes of bacteremia are Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus. E. coli and K. pneumoniae are increasingly exhibiting resistance to last-resort antibiotics, such as carbapenems. Rapid and accurate identification of these pathogens is critical for timely treatment and infection control. This paper aimed to develop a computer-aided bacterial morphometric technique for identifying and classifying wild-type E. coli, K. pneumoniae, and S. aureus in a field guide fashion. A 3D laser scanning confocal microscope was used to gather key parameters of each organism: length (L, µm), circular diameter (CD, µm), volume (V, µm³), surface area-to-cross-sectional area ratio (SA/CSA, unitless), surface uniformity ratio (Str), and surface texture ratio (Sdr). Microscope images and measurement results showed that S. aureus was spherical with the shortest length (1.08 µm) and smallest volume (0.52 µm³). E. coli and K. pneumoniae were rod-shaped with lengths >2.0 µm and volumes >1.0 µm³. Carbapenem-resistant (CR) strains exhibited larger volumes than their wild-type counterparts. Surface parameters further differentiated strains: wild-type E. coli had a greater surface texture or a less smooth surface (larger Sdr) than K. pneumoniae (lower Sdr) did. CR E. coli had more surface uniformity (lower Str) than CR K. pneumoniae did. A dichotomous key based on shape, circular diameter, volume, length, and surface characteristics was developed to classify the species using a series of paired, contrasting features. This morphometric analysis can aid researchers in quickly identifying bacteria, leading to faster diagnosis of life-threatening diseases and improved treatment decisions. Full article

Background: The Naples Prognostic Score (NPS) is a composite inflammation–nutrition index whose prognostic value has been scarcely examined in extensive-stage small cell lung cancer (ES-SCLC). This study aimed to evaluate the prognostic significance of the NPS in this setting. Methods: A retrospective analysis was performed on 142 patients diagnosed with ES-SCLC between March 2014 and June 2024. The NPS was calculated using the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), serum albumin, and total cholesterol levels. Patients were classified into three NPS categories (0, 1–2, and 3–4), and subsequently dichotomized into low-risk (0–2) and high-risk (3–4) groups. Survival outcomes were assessed using Kaplan–Meier estimates and multivariate Cox regression models. Results: Median overall survival (OS) was significantly longer in the low-risk group compared to the high-risk group (10.3 vs. 6.3 months; p = 0.012). High NPS remained an independent predictor of reduced OS (HR: 1.45; 95% CI: 1.02–2.06; p = 0.041). The prognostic strength of the NPS was primarily driven by low LMR and hypoalbuminemia, which were individually associated with worse outcomes. Conclusions: The NPS may serve as a simple, accessible, and independent prognostic tool in ES-SCLC, potentially aiding in clinical risk stratification and treatment planning. Full article

Background/Objectives: The COVID-19 pandemic highlighted the limitations of pulse oximetry in detecting occult hypoxemia. The superiority of the alveolar gas monitor (AGM) compared to pulse oximetry (SpO₂) in predicting respiratory deterioration among COVID-19-positive individuals has previously been demonstrated. Here, we combine COVID-19 and non-COVID-19 individuals as a combined cohort of participants to determine if the AGM has similar utility across a larger, more generalizable cohort. Methods: Adult patients (n = 75) at risk of respiratory deterioration in the emergency department (ED) underwent prospective assessments of their oxygen deficit (OD) and SpO₂, simultaneously measured during quiet breathing on the AGM. The OD and SpO₂ were then compared for their ability to predict the dichotomous outcome of the need for supplemental oxygen. The administration of supplemental oxygen was ordered by the clinical care team with no knowledge of the patients’ enrollment in this study. Results: In the logistic regression analysis, both SpO₂ and OD significantly predicted the need for supplemental oxygen among COVID-19-negative individuals. However, in the multivariable regression, only OD (p < 0.001) significantly predicted the need for supplemental oxygen, while SpO₂ (p = 0.05) did not in the combined cohort of COVID-19-negative and -positive individuals. Receiver operating characteristic (ROC) curve analysis demonstrated the superior discriminative ability of OD (area under ROC curve = 0.937) relative to SpO₂ (area under ROC curve = 0.888) to predict the need for supplemental oxygen. Conclusions: The noninvasive AGM, which combines the measurement of exhaled partial pressures of gas with SpO₂, outperforms SpO₂ alone in predicting the need for supplemental oxygen among individuals in the ED at risk of respiratory deterioration regardless of the etiology for their symptoms (COVID-19-positive or -negative). Full article

Objective: To analyze the association between physical activity, health-related quality of life (HRQoL), and perceived barriers to physical activity with the risk of symptoms of depression, anxiety, and stress in Chilean adolescents. Method: A quantitative, cross-sectional, descriptive-correlational study was conducted with a sample of 351 secondary school students (mean age = 15.75 ± 1.47 years) from several educational institutions in the south-central region of Chile. Validated instruments were used to assess physical activity (PAQ-A), symptoms of mental health (DASS-21), HRQoL (Kidscreen-52), and the short scale of barriers to physical activity. For exploratory purposes, mental health outcomes were dichotomized based on standard cut-off scores, and binary logistic regression models were estimated to identify associated factors. Results: Based on the binary categorization, a substantial proportion of students exceeded the risk thresholds for depressive (54.4%), anxiety (63%), and stress symptoms (42.2%). Across models, lower physical activity levels, reduced autonomy and weaker relationships with parents, and barriers related to self-concept and motivation were consistently associated with higher mental health risk. Additionally, passive commuting and the perceived school environment emerged as specific predictors of stress and depression risk, respectively. Conclusions: These findings suggest that individual and contextual factors linked to lifestyle behaviors and perceived social support may play a critical role in adolescent mental health, and could represent key targets for school-based interventions. Full article

Background/Objectives: Chronic obstructive pulmonary disease (COPD) is a progressive condition whose heterogeneous endotypes, clinical manifestations, and recovery pathways complicate the identification of reliable predictors of rehabilitation outcomes. Several respiratory and functional assessments are available with no consensus on the most predictive ones. While univariate markers may miss multifactorial interactions essential for prognosis, data-driven unsupervised clustering methods can integrate complex information from different sources. This study aimed to apply unsupervised clustering to identify pre-rehabilitation characteristics predictive of discharge outcomes for COPD patients undergoing pulmonary rehabilitation. Methods: A total of 126 COPD patients undergoing pulmonary rehabilitation were included in the analysis. Three assessments were performed at admission, namely the forced oscillation technique, spirometry, and the six-minute walk test (6MWT). The outcome was the change in 6MWT distance between admission and discharge. Unsupervised clustering methods were applied to admission variables to identify subgroups associated with outcomes. Results: Among the clustering algorithms tested, k-means (with N_cl = 2) provided the optimal solution. The resulting respiratory rehabilitation index (R2I) was significantly associated with the outcome dichotomized via the minimal clinically important difference of 30 m. Patients with R2I = 1, indicating severe functional and respiratory impairments, were associated with higher post-rehabilitation functional improvement (p = 0.032). While few functional parameters of 6MWT were statistically different between the groups identified by outcome, nearly all variables in the analysis exhibited significant distribution differences among the R2I clusters. Conclusions: These findings highlight the heterogeneity of COPD and the potential of unsupervised clustering to identify distinct patient subgroups, enabling more personalized rehabilitation strategies. Full article

Objectives: This study aimed to investigate the effects of physical activity and mental health on chewing difficulty in South Korean adults using data from the seventh Korea National Health and Nutrition Examination Survey (KNHANES VII, 2016–2018). Methods: A total of 8212 participants aged ≥20 years who completed surveys on their physical activity, mental health, and chewing status were included. Chewing difficulty was assessed via a five-point Likert scale based on self-reported discomfort when chewing due to oral problems, and dichotomized for analysis. The participants were divided into two groups: those aged <40 and those aged ≥40 years. Complex sample analyses, including cross-tabulations and logistic regression, were used to examine the associations. Results: Among men aged <40, high perceived stress was associated with 1.71 times higher odds of experiencing chewing difficulty (p < 0.05). For men aged ≥40, high perceived stress (OR of 1.45) and a sleep duration of <7 h (OR of 1.32) were significant risk factors (p < 0.05). In women aged ≥40 years, high Patient Health Questionnaire 9 (PHQ-9) scores (≥10; OR of 2.35) and high perceived stress (OR of 1.64) were significantly associated with chewing difficulty (p < 0.001). Conclusions: Perceived stress, insufficient sleep, and depression are significant mental health factors associated with chewing difficulty in adults. These findings emphasize the necessity of a multifaceted approach, including psychosocial mental health issues, to effectively manage chewing difficulty in this population. Full article

Background/Objectives: The question of whether the benefits of anticoagulation outweigh the risks of bleeding in patients with dementia and atrial fibrillation (AF) remains unresolved. This study aimed to evaluate the effectiveness of oral anticoagulation (OAC) and to compare the safety and effectiveness of direct oral anticoagulants (DOACs) with vitamin K antagonists (VKAs) within this at-risk population. Methods: This meta-analysis was conducted following the PRISMA guidelines and was registered in PROSPERO. Data were extracted from MEDLINE, Web of Science, and Cochrane Library. The Newcastle–Ottawa Scale was used to assess the risk of bias. The outcomes were analyzed using the Comprehensive Meta-Analysis software, with odds ratios (ORs) and 95% confidence intervals (CIs) calculated for dichotomous variables. Results: Eight retrospective studies were included, with sample sizes of up to 40,350 participants. The primary outcome was mortality incidence, while secondary outcomes included ischemic stroke, major bleeding, and intracranial hemorrhage (ICH). DOACs significantly reduced ICH events compared to VKAs (OR 0.38, 95% CI 0.17–0.84; I² = 87.3%) but showed no significant difference in major bleeding (OR 0.48, 95% CI 0.22–1.03; I² = 88%). Mortality and ischemic stroke rates were similar between the DOAC and VKA groups. OAC use reduced mortality by 29% compared to no OAC (OR 0.71, 95% CI 0.57–0.88; I² = 81.3%) but increased major bleeding risk (OR 1.19, 95% CI 1.08–1.3; I² = 0%). Conclusions: DOACs offer a safer profile regarding ICH in dementia patients with AF compared to VKAs, with no significant differences in mortality or ischemic stroke rates. This study highlights the need for careful anticoagulant selection in this vulnerable population. Full article

Background: Atrial fibrosis is a key contributor to atrial cardiomyopathy and can be assessed invasively using mean left atrial voltage (MLAV) from electroanatomical mapping. However, the invasive nature of this procedure limits its clinical applicability. Machine learning (ML), particularly regression tree-based models, may offer a non-invasive approach for predicting MLAV using clinical and echocardiographic data, improving non-invasive atrial fibrosis characterisation beyond current dichotomous classifications. Methods: We prospectively included and followed 113 patients with paroxysmal or persistent atrial fibrillation (AF) undergoing pulmonary vein isolation (PVI) with ultra-high-density voltage mapping (uHDvM), from whom MLAV was estimated. Standardised two-dimensional transthoracic echocardiography was performed before ablation, and clinical and echocardiographic variables were analysed. A regression tree model was constructed using the Classification and Regression Trees—CART-algorithm to identify key predictors of MLAV. Results: The regression tree model exhibited moderate predictive accuracy (R² = 0.63; 95% CI: 0.55–0.71; root mean squared error = 0.90; 95% CI: 0.82–0.98), with indexed minimum LA volume and passive emptying fraction emerging as the most influential variables. No significant differences in AF recurrence-free survival were found among MLAV tertiles or model-based generated groups (log-rank p = 0.319 and p = 0.126, respectively). Conclusions: We present a novel ML-based regression tree model for non-invasive prediction of MLAV, identifying minimum LA volume and passive emptying fraction as the most significant predictors. This model offers an accessible, non-invasive tool for refining atrial cardiomyopathy characterisation by reflecting the fibrotic substrate as a continuum, a crucial advancement over existing dichotomous approaches to guide tailored therapeutic strategies. Full article

Saproxylic beetles are key bioindicators of forest ecosystem quality and play essential roles in deadwood decomposition and nutrient cycling. However, their populations are increasingly threatened by habitat fragmentation, deadwood removal, and climate-driven environmental changes. For this reason, an integrated sampling method can increase the detection of species with varying ecological traits. We evaluated the effectiveness of integrative sampling methodologies to assess saproxylic beetle diversity within Sila National Park, a Mediterranean forest ecosystem of high conservation value, specifically in two beech forests and four pine forests. The sampling methods tested included Pan Traps (PaTs), Malaise Traps (MTs), Pitfall Traps (PTs), Bait Bottle Traps (BBTs), and Visual Census (VC). All specimens were identified to the species level whenever possible, using specialized dichotomous keys and preserved in the Entomological Collection TB, Unical. Various trap types captured a different number of species: the PaT collected 32 species, followed by the PT with 24, the MT with 16, the VC with 7, and the BBT with 5 species. Interestingly, biodiversity analyses conducted using PAST software version 4.17 revealed that PaTs and MTs recorded the highest biodiversity indices. The GLMM analysis, performed using SPSS software 29.0.1.0, demonstrated that various traps attracted different species with different abundances. By combining multiple trapping techniques, we documented a more comprehensive community composition compared to single-method approaches. Moreover, PaTs, MTs, and PTs recorded 20%, 40%, and 33% of the Near Threatened species, respectively. We report new records for Sila National Park, including the LC species Pteryngium crenulatum (Curculionidae) and the NT species Grynocharis oblonga (Trogossitidae). For the first time in Calabria, the LC species Triplax rufipes (Erotylidae) and the NT species Oxypleurus nodieri (Cerambycidae) and Glischrochilus quadrisignatus (Nitidulidae) were collected. Our results emphasize the importance of method diversity in capturing species with distinct ecological requirements and highlight the relevance of saproxylic beetles as indicators of forest health. These findings support the adoption of multi-method sampling protocols in forest biodiversity monitoring and management programs, especially in biodiversity-rich and structurally heterogeneous landscapes. Full article

Objectives: The present cross-sectional analysis aimed to investigate whether Large Language Model-based chatbots can be used as reliable sources of information in orthodontics by evaluating chatbot responses and comparing them to those of dental practitioners with different levels of knowledge. Methods: Eight true and false frequently asked orthodontic questions were submitted to five leading chatbots (ChatGPT-4, Claude-3-Opus, Gemini 2.0 Flash Experimental, Microsoft Copilot, and DeepSeek). The consistency of the answers given by chatbots at four different times was assessed using Cronbach’s α. Chi-squared test was used to compare chatbot responses with those given by two groups of clinicians, i.e., general dental practitioners (GDPs) and orthodontic specialists (Os) recruited in an online survey via social media, and differences were considered significant when p < 0.05. Additionally, chatbots were asked to provide a justification for their dichotomous responses using a chain-of-through prompting approach and rating the educational value according to the Global Quality Scale (GQS). Results: A high degree of consistency in answering was found for all analyzed chatbots (α > 0.80). When comparing chatbot answers with GDP and O ones, statistically significant differences were found for almost all the questions (p < 0.05). When evaluating the educational value of chatbot responses, DeepSeek achieved the highest GQS score (median 4.00; interquartile range 0.00), whereas CoPilot had the lowest one (median 2.00; interquartile range 2.00). Conclusions: Although chatbots yield somewhat useful information about orthodontics, they can provide misleading information when dealing with controversial topics. Full article

Purpose: This paper examines the differences between transgender persons who self-identify as bisexual (n = 4129) and those who self-identify as pansexual (n = 5056) when it comes to experiencing anti-transgender harassment, discrimination, and violence, serious psychological distress, and suicidal ideation. Methods: Data from the 2015 U.S. National Transgender Survey were used to evaluate the differences between bisexual and pansexual persons in a sample of transgender Americans aged 18 or older. The Kessler-6 scale assessed psychological distress, and a dichotomous measure of past-year suicidal ideation was used. A 20-item scale assessed the extent to which people experienced anti-transgender harassment, discrimination, and violence. Multivariate analysis and structural equation analysis were used to analyze the data. Results: Compared to their bisexual counterparts, pansexual persons experienced more anti-transgender harassment, discrimination, and violence, were more likely to experience serious psychological distress, and were more likely to report suicidal ideation. A structural equation analysis revealed that the bisexual–pansexual distinction is important when understanding transgender persons’ likelihood of experiencing suicidal ideation. It operates indirectly through its direct impact on the number of anti-transgender experiences incurred. Conclusions: Pansexual individuals fare more poorly than their bisexual counterparts on measures of anti-transgender experiences, serious psychological distress, and suicidal ideation. The bisexual–pansexual distinction is a meaningful one when trying to understand the transgender persons’ odds of thinking about dying by suicide. Full article

Background/Objectives: The aim of this study was to elucidate the associations between the use of various ASMs and systemic anti-inflammatory effects in a single large cohort using routine blood tests. Methods: Patients who underwent blood tests within three months of their first visit to our clinic were included. The systemic inflammatory index (SII, platelet × neutrophil/lymphocyte ratio), neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), and fibrinogen–albumin ratio (FAR) were compared across specific ASMs. Data from a total of 1782 patients with epilepsy were analyzed. Results: Multiple linear regression analysis revealed that valproate use was significantly associated with lower SII, PLR, and FAR values. Additionally, carbamazepine and oxcarbazepine use were associated with the FAR, whereas topiramate use was associated with the PLR. When a dichotomized category for each inflammatory marker was used, dividing the lowest quartile and the other quartiles, VPA use was significantly associated with all four markers. Topiramate use was associated with lower SII, NLR, and PLR values, and carbamazepine use was associated with lower SII, FAR, and PLR values. Conclusions: These findings highlight the closer association between valproate, compared to other ASMs, and systemic inflammatory responses. These findings may offer valuable insights into the underlying mechanisms of the therapeutic effects of valproate. Full article

Lactate, once regarded as a metabolic byproduct, is now recognized as a critical immunometabolic regulator that shapes immune responses in both physiological and pathological contexts. This review examines how lactate accumulation occurs across diverse disease settings, including cancer, sepsis, and diabetes, through mechanisms such as hypoxia, mitochondrial dysfunction, and pharmacologic intervention. We then explore how lactate modulates immunity via four integrated mechanisms: transporter-mediated flux, receptor signaling (e.g., GPR81), context-dependent metabolic rewiring, and histone/protein lactylation. Particular emphasis is placed on the dichotomous effects of endogenous versus exogenous lactate, with the former supporting glycolytic effector functions and the latter reprogramming immune cells toward regulatory phenotypes via redox shifts and epigenetic remodeling. The review also highlights how the directionality of lactate transport, and the metabolic readiness of the cell determine, whether lactate sustains inflammation or promotes resolution. After analyzing emerging data across immune cell subsets and disease contexts, we propose that lactate serves as a dynamic rheostat that integrates environmental cues with intracellular metabolic and epigenetic programming. Understanding these context-dependent mechanisms is essential for the rational design of lactate-targeted immunotherapies that aim to modulate immune responses without disrupting systemic homeostasis. Full article